Mortality prediction for acute decompensated heart failure patient using fuzzy neural network

Mortality prediction for acute decompensated heart failure patient using fuzzy neural network

It has been reported that patients admitted with acute decompensated heart failure (ADHF) face high risk of mortality where 30-day mortality rates are reaching 10%. Identifying patient with high and low risk of mortality could improve clinical outcomes and hospital resources allocation. This paper p...

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Bibliographic Details
Main Authors: Abu Yazid, Mohamad Haider, Talib, Mohamad Shukor, Satria, Muhammad Haikal, Harun, Habibollah, Abd. Ghazi, Azmee
Format: Article
Language:English
Published: Penerbit UTM Press 2020
Subjects:
Q Science (General)
Online Access:http://eprints.utm.my/id/eprint/90013/1/MohamadShukorTalib2020_MortalityPredictionforAcuteDecompensatedHeartFailure.pdf
http://eprints.utm.my/id/eprint/90013/
http://dx.doi.org/10.11113/mjfas.v16n4.1808
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Institution: Universiti Teknologi Malaysia
Language: English
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Summary:It has been reported that patients admitted with acute decompensated heart failure (ADHF) face high risk of mortality where 30-day mortality rates are reaching 10%. Identifying patient with high and low risk of mortality could improve clinical outcomes and hospital resources allocation. This paper proposed the use of fuzzy neural network to predict mortality for the patient admitted with ADHF. Results show that fuzzy neural network can predict mortality for ADHF patient with good prediction accuracy with overall accuracy of 88.8% for partition 50 and 90.40% for partition 80.

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